Cancer modeling and network biology: Accelerating toward personalized medicine

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DOIResolve DOI: http://doi.org/10.1016/j.semcancer.2014.06.005
EditorSearch for: Masoudi-Nejad, Ali; Search for: Wang, Edwin
TypeBook Chapter
Book titleSeminars in Cancer Biology
ISSN1044-579X
Volume30
Pages13; # of pages: 3
Subjectartificial neural network; cancer modeling; cancer therapy; mathematical model; network biology; personalized medicine; prediction; rating scale; systems biology
AbstractThe complexity of cancer progression can manifests itself on at least three scales that can be described using mathematical models, namely microscopic, mesoscopic and macroscopic scales. Multiscale cancer models have proven to be advantageous in this context because they can simultaneously incorporate the many different characteristics and scales of complex diseases such as cancer. This has driven the expansion of more predictive data-driven models, coupled to experimental and clinical data. These models are defining the foundations that facilitate the forthcoming design of patient specific cancer therapy. This should be considered as a great leap toward the era of personalized medicine. Consequently, further improvements in mathematical modeling of cancer will lead to the design of more sophisticated cancer therapy approaches.
Publication date
PublisherElsevier
LanguageEnglish
AffiliationNational Research Council Canada; Human Health Therapeutics
Peer reviewedYes
NPARC number21275781
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Record identifier7aa4eea8-1e00-4b79-9881-0c9e9cc9b5f1
Record created2015-07-14
Record modified2016-05-09
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